Generalization in Online Reinforcement Learning for Mobile Agents
Generalization in Online Reinforcement Learning for Mobile Agents explores Automated mobile agent training system with benchmark for zero-shot generalization, enabling a 7B-parameter VLM agent to surpass supervised fine-tuning baselines.. Commercial viability score: 7/10 in Mobile Agents.
BUILDER'S SANDBOX
Build This Paper
Use an AI coding agent to implement this research.
OpenAI CodexAI Agent
Lightweight coding agent in your terminal.
Claude CodeAI Agent
Agentic coding tool for terminal workflows.
AntiGravity IDEScaffolding
AI agent mindset installer and workflow scaffolder.
CursorIDE
AI-first code editor built on VS Code.
VS CodeIDE
Free, open-source editor by Microsoft.
Recommended Stack
Startup Essentials
Estimated $10K - $14K over 6-10 weeks.
See exactly what it costs to build this -- with 3 comparable funded startups.
7-day free trial. Cancel anytime.
Discover the researchers behind this paper and find similar experts.
7-day free trial. Cancel anytime.
Related Papers
- Builds On ThisPaying Less Generalization Tax: A Cross-Domain Generalization Study of RL Training for LLM AgentsViability: 2.0
- Builds On ThisCan RL Improve Generalization of LLM Agents? An Empirical StudyViability: 2.0
- Builds On ThisAdaptive Milestone Reward for GUI AgentsViability: 6.0
- Builds On ThisFrom Pixels to Digital Agents: An Empirical Study on the Taxonomy and Technological Trends of Reinforcement Learning EnvironmentsViability: 5.0
- Prior WorkUI-Voyager: A Self-Evolving GUI Agent Learning via Failed Experience